{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "initial_id",
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    ""
   ]
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-02T12:59:17.075910Z",
     "start_time": "2025-04-02T12:59:16.896312Z"
    }
   },
   "cell_type": "code",
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei'] # 指定默认字体为黑体 \n",
    "plt.rcParams['axes.unicode_minus'] = False # 解决负号显示问题\n",
    "\n",
    "\n",
    "# 生成原始误差数据\n",
    "np.random.seed(42)\n",
    "mu = 2.5\n",
    "original_errors = np.random.normal(mu, 1, 1000)\n",
    "\n",
    "# 中心化后的误差数据\n",
    "centered_errors = original_errors - mu\n",
    "\n",
    "# 绘制对比图\n",
    "plt.figure(figsize=(10,6))\n",
    "plt.hist(original_errors, bins=30, alpha=0.5, label=\"原始误差分布 (μ=2.5)\")\n",
    "plt.hist(centered_errors, bins=30, alpha=0.5, label=\"平移后误差分布 (μ=0)\")\n",
    "plt.axvline(x=0, color='red', linestyle='--', label=\"新分布中心\")\n",
    "plt.legend()\n",
    "plt.title(\"误差分布平移示意图\")\n",
    "plt.xlabel(\"误差值\")\n",
    "plt.ylabel(\"频数\")\n",
    "plt.show()\n"
   ],
   "id": "936351db81965fe3",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ],
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA0sAAAIgCAYAAABUAPJbAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/NK7nSAAAACXBIWXMAAA9hAAAPYQGoP6dpAABn2klEQVR4nO3dd3RU1d7G8WeSmVQghdBBEkAUVFARiUhVEJAiCIJgA0VEFKULFkBRUJQuqCBSFAQUpFwFC0250q+UUKV3aellMpOZ94+8GRhzQgKETEi+n7XOWmdO/U0ISZ7Z++xtcjqdTgEAAAAA3Hh5ugAAAAAAyI8ISwAAAABggLAEAAAAAAYISwAAAABggLAEAAAAAAYISwAAAABggLAEAAAAAAYISwAAAABggLAEAAXMzJkzlZiYeN3XuXjxombNmpVp+6effqrt27fn6BrJycm6ePGi6/WOHTu0YMGCq67ln3/+Uc2aNfXjjz/m6Hi73a7ExEQ5HI4rHud0OpWamqqkpKQrHrNjxw59/PHHstvtkqS4uDg9/fTTWrlyZbbXT05OvmIdGTVkXDs7aWlp6tOnj+bPn5/tsampqYqJibnqBQCQjrAEAAVIQkKCxowZo4cffljR0dGSpO7du8tkMmW5nDt3zvBa//vf/9StWzf9/PPPrm2JiYkaPHiw5syZk6N6vvzyS9166606f/68JOn333/XCy+84Kotp3744QdFRUWpSpUqOTp+y5YtKlKkiLy9va/43r28vOTr66vnn3/e7fx58+apR48eeuSRR1SyZEk99NBDWrx4sdavX+96X8uWLVPlypWvWMfRo0cVEBBwxToyali8eHGm848fP67z58+7BZn4+Hht2rRJ33zzjdv2ixcv6uTJk27BbN68eQoJCbnqJTfCNgAUBCan0+n0dBEAgNwTFxenpk2bqkSJEvrPf/6j3r17y2w2a9iwYW7HxcbGKjw8XHFxcSpatKgk6dixY0pJSZGPj48k6dVXX1Xbtm3VpEkTSdLXX3+tyZMna+3atfL19VVaWpq8vb0VHh6eqQ6bzaYqVaqofv36+uabbyRJKSkpuu2229S0aVN9+eWXhufs3btX/v7+MpvNru1t2rRRiRIlNH369EznOBwOWa1WhYSEqHTp0q77nD59Wr6+vvLyuvS5YP369dW8eXO99dZbktJbdVJSUuTv7+86V5JWr16tlStX6u6779abb76pkSNHqkOHDpLSA2P16tV17NgxtzrMZrMOHjyoW265xbXNbrfrxIkT8vf3l7e3d6baL68hJCRERYoUcduX8drPz891vcu/LpdLTU1VcnKyTp8+rbCwMEnS3Llz9dprr7nCqiTt379fP/74o3r06KHAwEC3a6xbt07169dXamqqLBaL4X0AoDAx/okLALhpFStWTMuXL1dCQoIkyWQyydfXV8HBwdme26dPH/3000/y9fWVyWSSlN4aFB8fr6JFi7qCR506deR0OpWWlqY6deoYdkebMmWKzpw5o/fee8+1zc/PT2PGjNETTzyhVq1aqW3btm7n/PPPP6pRo0aW9UVERGS5b9iwYRo+fLjrPocPH9bKlSv1wQcfuI7x9vZWYGCgKxgdP35cTZo00dy5c93CUuPGjdW4cWNJ0vvvv+92n9dff13FixfXoUOHXAGoa9eukuQWlKT0AGUUJHMq499QkkaPHq2NGzdq4cKFrm0//PCDxo8fr2XLlqlYsWKZzjcKPEOHDtXKlSvVqlUrlShRQlL690hQUJDrmKyCHQAUNoQlACggHA6H7Ha7fHx8FBoaqtDQUEnprSyTJk3SRx99ZHie1Wp1tSwtWrRIKSkpslgsrj+YFyxYoBdffFHnzp1ztThJ6c/OWK1WBQQEZLrmwYMH9eabb6pPnz6qVKmS274OHTqoc+fOevrpp7V8+XLVr1/fta9cuXJKSEiQr6+vvL29lZqaqpo1a+rBBx/U9OnTNW/ePPn4+Ojxxx/P9uuxd+9ejRw5Ug888IBatWpleMyIESP0zz//qFy5cm7bY2Nj5efn5wobDodDSUlJWrp0qWbNmqWFCxeqUaNGmjFjhmJiYrRs2TJt27Yt25quxrBhw/T333/Lz89PXl5eOnfunKKiotS9e3fXMWvWrJHdble/fv0kpf9bWq1WjR49WuHh4ZnC0vLly13POlWtWtW1/dFHH3V7Huzy1jgAKMzohgcABcSBAwd06623ul5brVa3cJNTkZGR2rhxY46O9fb2zjQwgdVqVePGjRUXF6ctW7a4upBdLjk5WY899ph+//13TZw4UT169DC8/vDhw/XZZ59p9+7dKl68uDp16qQiRYoYdscz0qJFC/3vf//Tnj17FBoaqttvv11t27bVhx9+qG3btql27doaOXKkBg4c6HZeUFCQnE6nzGazoqOjFRgYKKfTqeHDh6tFixaqVq2aXn/9dS1atEi+vr767LPP1Lx5c7dr/P333zKbzTnuzpYx0EPp0qUVGBioP/74Q3FxcfL3989xeElJSZHValWjRo0UFBSkxYsXq3v37jp//rwOHjyoyMhIJSUladOmTbrjjju0ePFivfDCC9q6davCw8Nd3fD40wAA0tGyBAAFRGhoqIYPH65Tp05p2rRp8vHxUWpqqs6fPy8fHx/DZ10yWodKly7t+oN86dKlMplMrj/yq1evrr59++rFF1/MdG5KSkqmbc8995yioqL05Zdf6uDBg1l26frkk080dOhQvfTSS5o/f76+//57hYSEuPavWLFCI0aM0NSpU5WcnKwTJ04oNTVVVqtVJ06ccLtWmTJlDO8zceJEVa9eXW+88YamTZvm2m6z2dStWzfdcccd6tu3b6bzYmNjJUn//e9/Va9ePc2cOdP1zFJycrJWrVqlixcvKjExUd99950efPDBTNeoXbu26zpXY/ny5WrevLmrxW3MmDEaNWpUtufdeeedWrNmTZb7X375ZTVs2NDVxfCNN97QqFGj9N13311XV0EAKMgISwBQQISGhmrYsGFas2aNq+Xlr7/+UoMGDeTj4yNvb2+lpKTIbrerSJEirmeOrFarjh8/rsDAQCUmJsrHx8cVnKKionT69Gk1aNAg0/28vb3l7++vU6dOKTg4WAEBAZo1a5YWLVqkJUuWqHfv3jp48OAVa96wYYMaNWqk/fv3uwWljRs36sknn5TD4XDrdpbh36PxHTlyRBUrVsx03K233qohQ4aoTZs2btszutlNnjw5ywETJGnChAmSpPnz52vbtm0KDAzU0KFDFR4erh49emjlypWaN2+eYVg6fPiw6+t+uZkzZ2rcuHGZhl9PS0tTfHx8pmeP7Ha7goODdeDAgSzrHDBggH7//fcs90vSd999J39/f508eVKTJ0/WgAED1KxZM7fWSACAOzolA0ABVqdOHVmtVsXHxysmJka9e/dWnTp1FBMTo9jYWCUkJMhms6l06dKaM2eOypQpo+LFi7uGkM5o3YiMjDQcYrp48eIqV66c6w/1559/Xrt27VKLFi20c+dO2e12DRkyRLfffrucTqdryTi+QoUK6tOnj6ZMmeKq+ddff1XTpk3VtGlThYSEaOHChbLZbLLZbOrSpYt69Ojheh0VFSVJ8vX1dZ1/7Ngx/fXXX9qzZ4/27t2rLl26qEiRItq7d69SU1N18eJFnT9/XjNmzFBAQID27t2r7du3a9OmTUpOTnZdZ8OGDVq9erWqVq2qcuXKafz48fL399eWLVv0999/6+jRozp79qw+/fRT1zDg9957r+v8kJAQBQYGys/PTz///LMsFov8/PxkNptlMpnk5+cnPz8/HTt2TH5+fq6BJ/79DJjFYtHhw4cVFhaW5TJlypQrdveLjo7Wt99+q86dO+uOO+5Qw4YN9eeffyogIECVKlXSQw89pDfffDNTSyEAFHa0LAFAAXbo0CElJye7wsTRo0fl4+PjaqVwOByy2WwymUx64YUX9Pzzz8tsNsvLy0s//vijWrdurd9//1316tUzvL7D4VBqaqpb60lGS4W/v7+k9Napu+66y+28kydPymw2u41AJ6V3AWzXrp3atGmjOXPmqGzZsvLy8nK1/mSEkozXGfe9vHXo888/19ixYw2flYqPj9fs2bPdJsbNeFYoNTVVu3bt0u23367Y2Fg99dRT6tWrl5YsWaL77rtPderUUXR0tG699Vb16NFDv/zyi1uLVr169fToo49muuePP/6otm3b6scff8y0f8WKFWrXrp3Wrl2r+++/3/BrbLPZVLFiRW3atMlwv5Q+GMTmzZuz3B8QEKDFixcrMjJSY8aM0QsvvKDBgwerR48eevvtt/Xdd98pNTXV8GsGAIUZYQkACrB+/fpp9erVrtaMCxcuSEpvcTKZTK5ueGXKlHHrMrdr1y4999xzqlevnsLCwnT48GHXUOJSesCwWq0KDg7OFHguFxsbq9WrV2v06NFu20+ePOkKQpdr2bKlpk2bpmefffaK3eOuZOTIkRo5cqThvjvvvFOtWrXShx9+mOX5NptNzZs3V2Jiovr3768lS5ZIkjp37iyr1ao6deooKSlJM2fO1IwZMzRs2DCtWrVK27dv1w8//OB2LafTqXfeeUfNmzc3DFLNmzfXE088obZt22rLli0qW7ZspmNSU1N1+PDhK36dHQ7HFYdc9/X11YoVKySld+v76quvNHnyZPXq1UufffaZ65modevWZXkNACiMCEsAUEBt3LhRo0ePdg0RvWHDBtWtW1fFixfXsGHD9Oqrrxqet2nTJrVq1UqVKlWS3W7X3XffLV9fX1frS8Yw4ykpKerXr1+WwURKn6PI6XTqySefdNt+8uRJVahQIdPx3t7eev75512vHQ7HFd9jdvuvhcViUf/+/SUp0/NDvr6+mj17tsqXL6/k5GQ988wzOnv2rJYvX6633nrLNW9RhhkzZmjPnj1uLVn/9vnnn6tOnTp6/PHH9fvvv7uNYHj69Gm99dZbGjJkiNatW6eqVauqdOnSGjx4sB555BHXZMFSejD9+eef1axZsyzv5XA4VK1aNZUvX16PP/64Nm7cyDNLAHAFPLMEAAWQw+FQ69atNXv2bEnpk5u+8MIL6tKliz788EO99dZb2rlzZ6ZzJkyYoPr166tu3bpatWqV/vzzT6WkpCg2NlbDhg1TtWrVFBMTo5iYGKWkpFwxKI0ePVpjxozRRx995DZ4gyTt27fPMCz9m9VqzXL7yJEjNWjQIFksFrcJVXNDhw4dXKPf/XsY7Ro1aig0NFTlypVzDW1es2ZNvfHGG27HHTp0SP369dOwYcNUpUqVLO8VEBCg77//Xjt37sw0Ml+bNm00fPhwOZ1ONW7cWCtXrpSXl5esVquee+45paSkaPPmzbJarVq5cqVat26tP/74w3V+Wlqa2/W8vLz0/fffq0GDBho3bpzuuOMOzZw5M1NNNyKEAsDNiJYlAChgNm/eLKfTqU6dOmnEiBGKiYlR+/btlZiYqI8//lhlypTRypUr1bBhQ02dOlXt27eXyWTS0KFD9fHHH+vDDz9Us2bNdOjQIbdWjnPnzik1NVV79+51bbPZbLJarbrvvvtc2/bs2aN3331X8+fP1+DBg/XKK69ISv8D/IMPPtDx48f1888/65NPPsn2vfw7LDkcDjmdTvn6+mrlypXat2+fPvrooxzPZZSWlnbVcwjZ7XbXXFKJiYk6dOiQoqKi9J///EffffedXnzxRU2ePNmtm6IkffDBB4qIiNCAAQOu+J4k6bbbbtO4ceO0fPlypaamysfHRzt27ND//vc/fffdd7JYLCpWrJji4uIkpbfYPf/88/Lx8VGPHj1UvHhx/fbbb3r55ZfVsWNHbd++XSVLlpTdbpfD4XAbSS8wMFDPPPOMnn76af3222+qWbOma//Jkydd7/la5ugCgALHCQAoUL799ltnixYtnIcOHXK+++67ztKlSzurV6/u3L9/v+sYm83m7N27t9NkMjmrVavmHDt2rNNutzv37dvndDqdzmbNmjmLFi3qDAoKuuISGBjoDAoKcl03MTHRee+99zrLlSvn/O677zLV1qNHD2eVKlWcgwcPdlqt1qt+bx07dnQ+//zzTqfT6UxNTb3q8yMiIpx9+vS5qnMqV67s/Oyzz5x2u91Zt25dpyRn0aJFnV26dHH++eefWZ7ncDicp06dcr1esWKF85FHHnGGhIQ4H3rooWzvO2TIEGfz5s1drx966CGnyWRySnJbgoKCnD/99JPT6XQ6rVarc8qUKc60tDSn0+l0zpkzJ9PxOVkSExOv6msEAAWVyelkmm4AKGgcDofi4uJUr149PfnkkxowYIDhSGf/+9//9MEHH6hXr156+OGHc+Xe//zzjwICAlzPNuWmtm3bqkiRIvrmm2+u6fxy5cqpbdu2mjx58jWdv3//fh0/flwNGjTIcWtWhsTERHXo0EF16tTRK6+8kun5JiNWq9VtWPSrNXv2bPXr10/nz5/P0fHr1q1T/fr1FRsbm+l5LQAojAhLAAAUUPHx8Tp//rwiIiI8XQoA3JQISwAAAABggNHwAAAAAMAAYQkAAAAADBCWAAAAAMAAYQkAAAAADBSaSWkdDodOnTqlokWLZpo4EAAAAEDh4XQ6FR8fr7Jly8rLK+v2o0ITlk6dOqUKFSp4ugwAAAAA+cTx48dVvnz5LPcXmrCUMTni8ePHmWgPwNWx2aQZM9LXu3WTrnIyUgAAkL/ExcWpQoUK2U6gXmjmWYqLi1NQUBCzkgO4eomJUpEi6esJCVJgoGfrAQAA1yWn2YABHgAAAADAAGEJAAAAAAwQlgAAAADAQKEZ4AEAAKAwSUtLk81m83QZgEdYLBZ5e3tf93UISwAAAAWI0+nUmTNnFBMT4+lSAI8KDg5W6dKlr2uOVcISAABAAZIRlEqWLKmAgIDr+kMRuBk5nU4lJSXp7NmzkqQyZcpc87UISwCQHV9f6T//ubQOAPlUWlqaKygVL17c0+UAHuPv7y9JOnv2rEqWLHnNXfIISwCQHbNZatnS01UAQLYynlEKCAjwcCWA52X8P7DZbNcclhgNDwAAoICh6x2QO/8PaFkCgOzYbNKcOenrTz0lWSyerQcAAOQJWpYAIDupqVK3bulLaqqnqwGAQsvhcGQaDn39+vXat29fpmN37NiR5XW2bt2qf/7557pqcTqdbq/tdnuOzktLS3OtHzt2TImJiTm+5969e3N1OPhDhw7p22+/zbXr3WgrV67Uxo0b8/SehCUAAAB43L333quSJUsqPDz8isu7777rdt7UqVP1n4xBeP7fwYMHdc8992jbtm2G91q4cKEaNWqk06dPS5JKlCihihUrut0nJCREo0aNMjz/wIEDuueeexQfH+/a9vrrr+uNN9644nu8ePGiIiIitH//fknS888/ry+++OKK51yudevW+vjjj3N8/JUkJSWpffv2KlWqVK5cLy+UKVNGXbt2ve6gezXohgcAAFDAjft1f57er2/Tqld9jsVi0dSpU9W2bVvXtqZNm2rq1KmKiIjI8rxjx47p+eefd9s2bdo0de/eXXfffbeio6MVEhLitv/999/X7t279cYbb2j27NmyWCzat2+f/Pz8XMd8+OGH8v3XCKhWq1U+Pj6qUqWKIiIitHnzZj300EOKiYnRggULtHbtWknprUxeXl7y8nJvl5g0aZLKli2rqlXTvz4jRoxQy5Yt1alTJ5UrVy7Tvby8vGQ2m2UymbRmzRr9888/evXVV92OczqdrtYqsznnf9p/+OGHateunR566KEcn3O1/vzzT/Xo0UP79u1TxYoVNWPGDNWvXz/b81577TVNmjTJ9bpy5co6cOCAqlevriFDhmjIkCH66quvbljdlyMsAQAAwOP+/TD+qVOntHXrVpUvX97w+PXr12vJkiXavn27FixYoJ9//lnt2rVTeHi4Fi1apI0bN8rpdKpFixZ6+eWX9dxzz7nO9fLy0ty5c5WQkGB4byNpaWkqV66c/P39XSOrdezYUUlJSSpZsqQCAwP16KOPyul0KjU1VcuWLdN9993nOv/YsWMaM2aMWyvYAw88oFatWqlTp05asWKFihQp4trXqlUr/fe//5XFYpHJZFJsbKwCAwN1yy23GNb3/vvvZwpSWUlISNCcOXMUFRWVo+OvRWxsrNq1a6dhw4bpiSee0AcffKAuXbro2LFj2X69t2zZoh9//FF169aVJLeR7J555hlNmDBBR44cUXh4+A2rPwNhCQAAAPnGtGnTNHDgQJUvX15ly5bVPffcI0mKi4tTuXLltH79ekmXWlHsdrvKlSunr7/+Wvfff78mTZqkjz76SCEhIXI6nfrkk0/UsmVL3X333apZs6aOHj3q6j5XrVo1SektF5cHmwx9+vRxrXt7e+vs2bNyOByuew8dOlQxMTGaOHGi67iMZ4oslw0G5HQ69cILL6hly5Zq0KCB2z0+/fRT1a1bV82bN9fixYsVFhYmSfr1119dxyxcuFBDhgzRX3/9pTFjxrjufa2WL1+uFi1auOYiulavvfaaZs+enWl7jx491KFDB73++uvq1auXpPRuihMmTNC5c+dUsmTJLK9pt9u1a9cuNWjQwC08ZjCZTHryySe1cOFC9e/f/7rqzwnCEgAAAPINi8Wi5s2ba968eW7bv//+e3366aeu17Vr15bdbtfmzZs1ePBgLVu2THv27NGsWbO0bNkydevWTQEBASpevLiqVKmi9u3ba9euXVq6dKl+/PFH/fzzz4qPj5evr69++eUX+fr6urV4ZLQQ2e12Vzhav369Hn/8cVfIOHnypEqUKKGlS5e6zrPZbOrcubM++eQT17YBAwZo3759mjlzpmw2m9t9AgIC9Msvv6h169a6/fbbNXHiRHXp0sW1/8iRIxo4cKAWLVqkwMBApaSkXPeQ2Dt27FCdOnWy3D9z5kxt27ZN48ePlyQNHz5cd999t1sXSUkaNmyY+vXrl+n8YsWKKTQ0VPfff79r2759+xQcHOwKg1nZuXOnHA6H7r77bp08eVINGzbU1KlT3VrUIiMjNW3atBy80+tHWAIAAEC+kBECVqxYoTvvvNNtX1xcnCpVquS2bcuWLbr33nslpf8x/uKLL6po0aJ68MEHddttt7k9g7R06VL5+vqqd+/e6t27t0wmk8xms+bNm6dRo0bJYrEoNjZWFy9eVKVKlVwj702cOFFNmzaVzWbTAw884Bpc4OjRo6pZs6b279+fqQUk41yLxaL58+dr+vTpeu+997LsUihJX3/9tVavXu02qt7JkyfVvHlzHT9+XI0aNZIkpaSkSJImT57sOm7+/Plq1qxZjr7GknT27NkcPTuUneLFi6t48eI5OnbUqFHq0aNHpue4/m337t267bbbNGnSJIWFhalv377q0aOHVqxY4TqmZMmSOnv27HXVnlOEJQDIjq+vtGDBpXUAQK5LTExU0aJFdfHixSxbli7v7ialt/S0adNG+/btU/ny5RUaGurq9vVvbdq0Mdz+zDPP6JlnnpEkff7551qxYoUWL16c6bh+/fpp8eLFrudnTpw4odDQ0EyhTkoPS+3atdOECRPUqVMn1alTRxUqVNCLL76oFStWaPjw4dq6davr+IoVK6pKlSp6+umnXdu2bNmi9u3b67HHHtPs2bMVExMjSXr77bclpT+jJKW3slz+TE9OBAYGup7XygtffPGFDhw4oCVLlmR77FNPPaWnnnrK9XrKlCmKiIhQXFycihUrJin9mSujLno3AmEJALJjNktPPOHpKgCgQDtz5ozCwsL0zz//aMOGDQoPD1dSUpLi4uJUunRpSVKNGjXczlm3bp2eeuoprVy50jWqW7t27bR06VK3rmppaWn66aef1KJFi0z3veOOOxQdHS0fHx9FR0fLarW6Bg5ISkqSlN4SM2nSJNcIbcuWLdOgQYO0efPmHP3RnnE9f39/7dy5U3fddZera19aWpr++ecfVahQwXV8amqqXnrpJb388svq2rWr4XNBl7uaUfCk9HB28ODBHB9/+dxQl7vSM0ujR4+WlN5SNHDgQP3www8KDg6+qjql9FYkh8Oh06dPu8LSwYMHsxzoIrcRlgDgeqw2noPjqjQecv3XAG6A3Bhu+lqGkEbhc/78eV24cEEVK1ZUjRo11KRJE5UoUcL1nNKaNWsUExOT6Y/tKVOm6L333tPhw4ddk6v6+Pho+vTp6tq1q+u4O++8061LXoZFixbpp59+UsWKFRUTE6MqVaooNDRUkyZNUqtWrQxrXbNmjXr27Kny5csrPDxcRYoUUWxsrIoWLeoate6XX35xe14ng8Ph0Lfffqu33nrLte2ff/6RyWRyBcKM97Bx40aZzWadOXPmar6UOdKsWTO9+OKLGjhwYI6Oj46ONtx+pWeWpPR5pR5//HENGjRIDz/8cI7uNXDgQN1zzz2u57bWr18vLy8vtzC5bNkyt9ENbyQmpQWA7Njt0nffpS85nKEdAJBzq1atUs2aNRUUFKTjx4+revXq2rlzp2t/dHS0br/99kyTz7Zq1UqPPPKIqlSpop49e+qnn37KcvCDy7dnjFjXp08fnTp1SjabTc8884xatWqlmTNnqmfPnpmG1U5LS9OoUaP0xBNPaMGCBdq4caPOnz+vI0eOyGazadWqVTp69KhiYmIMg5IkvfPOO0pNTVWHDh1c206cOKHSpUtn6kqX0VqUUeu/nTx5Ut9//70OHz6sokWLGh6Tldtvv11ms9k1L5SRP//8U3a7XQ6HQ2vXrnV1A7xc8eLFDScODg0NlcPhUMeOHRUeHq7XX39dCQkJSkhIcLVSJSQkyGq1ZrpmzZo19fbbb2vlypX65Zdf1LNnTz377LMKCAiQJP3999/asWOH6xmuG42WJQDIjtUqdeyYvp6QkN4tDwBuIvm9hW/evHlq2rSpjh49qlatWunVV1/VXXfdpb1790qSQkJCNG/ePLVv317Tp093jco2c+ZMfffdd9q0aZP279+vhIQEOZ1O9erVy23Y7/j4eDmdTtfr9evXKyAgQMuXL1daWpoaNWokk8mk+fPnKyAgQEOHDlX9+vXVq1cvdenSRXfccYc6deqkLVu2aOXKlbrrrruu+H6cTqecTqdrMIOYmBgNHjxYS5cu1cqVK+Xn56eEhATt2bNHX375papXr57ltRwOh9sgChmj6ZlMJvXt21ft2rVTzZo1r/ZLrgkTJuipp57S77//nmnSXil9CO9GjRrJZrPp/vvvV79+/VSxYkU1btw4R9ffuXOnVq5cKelSS5MkrV69Wo0aNVKrVq3Utm1bt38nSXr66ae1a9cutW/fXt7e3nr66ac1cuRISendE1944QWNHj36qrseXit+4wMAAMBjtm/friVLlmjnzp2aO3euOnXqpLffflvjx4/XxIkTdffdd0uSGjVqpO+//971rM3WrVs1fvx4/fLLLypWrJhrnqSJEydqypQpmbrhXd6K0aBBA+3cuVNnz55V8+bN1adPH7355pvy8fGRlP7MTa1atTR48GAdO3ZMX3/9tT766CMVLVpUv/76q2rXru02R5HJZHLd3+l0KiUlRV999ZWeeuopJSUlqX79+goLC9O6detcI/r5+PioS5cuKlu2bKaBKy737+eLMsJS2bJldfz48Wv+uteoUUP9+/fXmDFjXINFXK5BgwYaO3asUlNT5efnp+nTp1/V9WvWrOkWUP9tzZo1We4bNWqURo3K3M39m2++UZMmTa5q5L/rZXJe6V0UIHFxcQoKClJsbKxbugWAbCUmShkP8CYkSIGBl/bxzBIKMJ5ZuvmkpKTo8OHDioiIMHxGJ7/avn17ptaRHTt2aPv27Xr00UezHJ7a6XRm6naXmJgoi8XiCj7ZSU5OvuLkrEb3uFrnzp1TiRIlrusaN4rD4cg0nPe/51nKL6723+JK/x9ymg089szS+fPnFRERoSNHjri2RUVFqXbt2goJCdHAgQPd0ujatWtVrVo1hYWFaezYsR6oGAAAADeCUTeyGjVq6JlnnrniPD5GfzgHBgbmOChJumJQyuoeVyu/BiVJhvMede3aNd8FJSl3/i2ulkfC0vnz59WqVSu3oGS1WtW6dWvVqlVLW7Zs0e7duzVz5kxJ6Wm8TZs26ty5s9avX685c+Zo9erVnigdAAAAQCHhkbD05JNPuoYDzLB8+XLFxsZq7Nixqly5skaOHOnqGzlnzhyVLVtW77zzjm699VYNHTr0qvtNAgAAAMDV8EhYmjZtml577TW3bdu3b1dkZKRrWMAaNWpo9+7drn2NGzd2Nb3df//9brMeG7FarYqLi3NbAAAAACCnPDIaXkRERKZtcXFxbttNJpO8vb0VHR2tuLg4tyEVixUrplOnTl3xHqNGjdK7776be0UDKLx8fKQZMy6tAwCAQiHfTEprNpvl6+vrts3Pz09JSUmZ9mVsv5IhQ4YoNjbWtVzP0IoACjmLReraNX2xWDxdDQAAyCP5JiyFhobq3Llzbtvi4+Pl4+OTaV/G9ivx9fVVsWLF3BYAAADkT6mpqVfc73A43OZKulxcXJyWLVum77//XpKUlpamF154QZs3b77metLS0jJtW7t2rRITE6/5mpIyzT1kt9uvup69e/fK4XDk+J67du26quOzs3HjRv3222+5dr2cmj9/vg4dOpSn98w3Yal27dpav3696/Xhw4dltVoVGhqaad9ff/2lcuXKeaJMAIWR3S79+GP6ksNfagCAnIuNjVVQUJCCgoIUHBys4OBg+fr6ytfX1/U6ODhY999/v+ucmJgYNWvWTFWrVlVoaKiefPJJffvtt3I6nVq4cKEWLFigihUrZnlPm82m6OhoHT9+XFu2bNGSJUs0ZcoU9evXT82bN1eJEiW0bNkyt3O++OILNWvWTAkJCUpMTJS3t7fCw8PdlqJFi+rbb781vOcff/yhRo0auQWfdu3aafLkyVf8+uzdu1cRERGKiYmRw+FQmzZttHjx4hx8ZdPnGoqMjNS8efNydHx2zpw5o+eee05lypTJletdjZIlS6pDhw5KTk7Os3t65JklIw0aNFBcXJxmzJihbt26aeTIkWrSpIm8vb3Vpk0bvfLKK/rtt9/UsGFDjR49Ok9n7gVQyFmtUqtW6esJCZI53/zoBICcyY0JtK/GVU62HRQUpOTkZFmtVtejF3369JEk13w/x44dc/uwPDg4WDVq1FCLFi00c+ZMjRs3To0bN1ZKSoqGDx8ub29vPfTQQ5LSB/4aO3asWrdu7XZ+iRIlFBISoqCgIJUqVUplypRRuXLlVKdOHQ0dOlSVKlVyq3P69Olq1KiRRo8erbffflslSpRwmwpHknr27Ok2AarT6VRqaqp8fX31wAMPyOl0at++fapevboOHDigDRs26KuvvpLT6ZTNZpPFYsk0n9BHH32kunXrKjg4WJL03nvvaeDAgXrkkUdUJGPS9P+XkpIib29vWf6/2/i8efNUsmRJderUye04p9Mpu90uLy8veXt7Z/dP5DJo0CC9+eabuuOOO3J8ztWKiopSt27ddODAAXXv3l2jR4+WyWRS48aN1bZtW3388ccaOnToDbv/5fLNb3yz2awvv/xSnTt31sCBA+Xl5aU1a9ZIksLCwjRu3Dg9+uijKlKkiIKDg11zMAEAAODmN3HiRG3ZskWzZ8823P/000+rXr16GjlypGvbxx9/LElasWKFK2B0795dwcHBGj9+vB555BGtW7dO3bt3V4sWLdyu53Q69dtvv6lKlSo5rtHf31//+c9/FBAQkOMJUo8cOaL7779f/v7+rglg69atK4fDodDQUAUGBqp27dpyOBxKTU3Vjh07VLJkSdf5mzdv1vz587Vz507Xtk6dOumzzz5T165dNW/ePJkv+xCvRo0aOnnypCwWi5xOp+Li4lS0aNEsJ/edPXu22rRpk6P3cvDgQUVFRWnWrFk5Ov5aZMy92qxZM82bN0+vvfaaZs6cqW7dukmSBg4cqBo1amjAgAGuUbRvJI+GpX/32WzTpo0OHjyorVu3KjIy0u0ftWfPnmrWrJn27t2r+vXrZ0rRAAAAuHk1bdpUgwYNUocOHTL98f7f//5XGzZscJtnc8mSJXr77bcVGBio3bt36+WXX5bT6dRnn32m22+/XQMGDNDEiRMVFRWVKVBI6d3wkpKSlJCQkGVNaWlpMplMKlasmP7++29ZrVZ5e3urWrVqSk5OVlhYmO68885M511ef0REhM6cOSNJrhacZ599Vnfffbf69esnSa5WJS8vL7c6U1JS1K1bN73++uuqXLmya7vJZNI333yjyMhIderUSbNnz1ZgYKAkaf/+/a7jPvnkEy1ZskRr167VSy+9pLp167pCx7VYtGiRunTpkuOgmJW2bdu6GkUu9/7776t8+fKuuVcDAgI0cuRIvfLKK666/f399cgjj2j58uVq3779ddWRE/mmZSlD6dKl1bJlS8N9ERERhsOOAwAA4OZWrVo1DRgwQL1791aTJk1c29PS0tS7d2+98soruvXWW13bH3vsMT322GM6deqUKlSooM8++0yNGjWSlP7se5EiRfT777/rhx9+0H333ZfpfmlpaapXr56rtceIzWZTq1atNH/+fM2cOVP//e9/FRUVpfPnz8vLy0tbt27NNJpzRguRw+FwXXvBggXq27evq3ve0aNHtWbNGk2cOFHSpS5xgwYN0uuvv+6q79lnn5XFYtHgwYMzDQRRpkwZrVy5Ui1btlT16tU1bdo0PfLII679W7Zs0ZQpU7R27Vp5eXkpMTExx4NJZGXHjh3q0aNHlvuHDx+u4OBgVxfKrl27qk+fPrr77rvdjvviiy8MnzsKDQ3VuHHjspx7NUNkZKS2b99eOMMSgAIuN/rNX2VfeCCvjPt1f/YHZaNv06q5UAlwc+rXr5+WLl2qixcvurb9+eefOnPmjIYPH254zldffSWHw6G5c+e6Asfu3bvVpUsXXbhwQefPn890Tnx8vJxOpw4cOODW5e1KPvjgAx05ckSRkZGSpHHjxunrr7+W2WzWuXPnlJqaqvLlyystLU2pqalavHixqlWrptTUVD355JPq3LmzpPRBHp577jkdPHgwUwuNw+GQ3W6X2WzWJ598ovXr16tnz56uZ5WM/PLLL5o4caLbSNG7d+9Wq1atFB0drbvuukuSlJSUpMWLF2vgwIGu49avX69q1arl6P1L0tmzZ1WqVKkcH5+VK13jSnOvhoSESEof6OG///3vddeRE/lmNDwAAAAUPk6nU1arVU6nU6Ghodq6davKly/v2l+/fn3t2LFDQUFBSktLU0pKiutRjpiYGE2ePFm33nqr4uPj9dJLL2n48OE6duyYvL29lZycrAEDBujOO+/UAw884BqFLjo6WmazWWFhYapTp47CwsIMl7fffjvLugcPHqxdu3Zp+/btevbZZ/X0009r27Zt2rlzp/bt2+cKIR07dtQtt9ziGi2vQYMGSklJUURERKaR9CpWrOga0KJ///5av369Bg0apOTkZI0bN06tW7eWzWaTzWZTYmKiTCaT7rrrLi1btszVqvbzzz+rQYMG6tChg6pVq6aYmBjFxMSoY8eOmjhxouu1n5+faxCInAoMDLxit8XccKW5VzMkJCTk2SM5tCwBAADAY/bv36+777470x/IGd20Lh/Uy263y2az6dixYypVqpReffVV1atXzxWU7rvvPtWsWVNDhw7V//73P0VHRys4OFiTJk3Sn3/+6XpmaP/+/brlllvk5eWlpKQkrVixIlNXveHDh7v9gf5vxYoVU9GiRWWxWHTu3DmZTCYtXrxYTqdTiYmJCg8P15YtW9yG+P7000/13XffadWqVdmOQGc2m12h0WKxaMeOHapRo4brmaYTJ07IYrG4tdJcuHBBvXr10vjx41WlShWtW7cu23tcjYoVK+rgwYO69957c3S80VxV0pWfWQoNDVVUVJTb9n/PsXrw4EHdcsstOS/8OhCWACA7Pj7Sp59eWgcA5JrbbrvN8PmVfw8d/m+//vqrFi1apKioKPXq1UtSemvM9OnTtX//fn3yySd66aWX9Pnnn2vMmDFasmSJ69zNmze7/uC/0jNLWe2bMWOGjh07puDgYB06dEj33HOPihUrpsWLF2d6PifDvHnzNGbMGAUEBKhMmTLy9/dXbGysgoODlZaWptjYWP3999+GXdQSEhK0ZMkSt/dw6tQplS1b1q0rX/HixbVv3z6ZzWZt2LAhy/d1rZo1a6Y5c+boiSeeyNHx0dHRhtuv9MzSli1bNG3aNNe2y+dezbBs2TLNmDHjKqu/NoQlAMiOxSK98oqnqwAAXKZp06batm1bprmQXnjhBT3//POS0lty7rjjDj333HOqWbOm65i5c+e6BlK4mpHdbDabzp8/r+HDh+vBBx+U2WxWx44d1bdvX1WpUkVPPvmkfvvtN7duhCkpKRoyZIi+//57/fbbb7rtttskSefPn1eJEiV0/vz5K7bwOBwO9erVS9WqVVO9evVc20+cOOF2nwwZ17LZbIbXO3DggDZt2qTo6GgVLVo0x+9dkh5++GENGDBAf//9t9tgG5f7/fff1adPHyUlJWnjxo2KiYnJdMyVnlm60tyrkrR27Vr5+fld1ZDv14OwBAAAgHwnqy5cl6tatarr2MuPP3XqlH7++Wdt27ZNjz/+uD744APXvpkzZ+rw4cPq0KGDpPQw0rJly0zP78TFxWUa+W3Dhg0KDQ3V6tWrdeTIEbVt21bVq1fXO++8I29vb+3fv1/33nuvBgwYoA4dOqhixYpq2LChUlNTtW7dumy7jmU8i5UR4E6fPq1evXpp3759WrlypSTp4sWLOnDggL755htVr149y2uZTCbXgAhSeniy2+06f/683nnnHQ0cODDLuZeyYrFY9PHHH+v555/Xb7/9lqnrpCSdOXNGDRo0UEJCgtq0aaN27dpp06ZNWYarf7vS3KsxMTHq3bu35s6de1V1Xw/CEgBkJy1N+uOP9PX69aWrmOkcAPKFm3AU0eTk5By3+qSkpCglJUW7du1S/fr1lZiYqCZNmmjq1Kl6+OGH3Y6tV6+e5s2b5xphzmq16scffzR8ZiljfqQMzzzzjB588EFt3rxZr732mt5++229+uqrrjrfe+89NWzYUG+++abi4uL0/vvva9q0aapcubLGjx+vESNGuIYPl9IHTAgLC5OUHpSSk5O1evVqPfjggzp79qzuvfdePfjgg1q7dq1KlCjhOq5ly5a6//779eabb2b5NalXr55Wr17tep0xMERkZKQOHjyYo6+rkRYtWmjjxo2aPXu2XnzxxUz7O3bsqFdffVUOh0M+Pj5uc2PlVFZzr44dO1b9+/c3nNvqRjE5/z0zbAEVFxenoKAgxcbGqlixYp4uByi8bsahwxMTpYxRdxISpP+f+E/Szfl+cMMUtKHDC9r7KQxSUlJ0+PBhRUREuP1RXpisW7dO99xzj2uS1uycOXNGxYsXv6qR4TJG8LvS19jpdF735K3nzp1zhaT8xuj9/Xuepdx2+dxVOXGl/w85zQa0LAEAAKDAuPy5npwoXbr0Vd/DZDJlG0avNyhJyrdBSTJ+f1nNhZVbriYo5do98/yOAAAAAHATICwBAAAAgAHCEgAAAAAYICwBAAAAgAHCEgAAAAAYYDQ8AMiOxSKNHn1pHQBwwyxZskR//vmnPvroI7ftFy5c0OHDh7Vu3TrZbDYNHDjQbX9aWpq8/38evJSUFJ0+fVoRERE5uue5c+eUlpZ2TSPjXYuTJ0/K19fXNccS8i9algAgOz4+0sCB6YuPj6erAYACKTExUQ6HQ3a7XUuXLlVaWpqSkpKUlpamWrVqKSwsTI0bN9a0adO0atUqxcXFuZ3/7LPPavT/f7D1/fffq23btjm+99SpU9W4cWOlpaVdVc3x8fEymUzas2fPVZ3Xu3dv9e3b96rOgWcQlgAAAOBxQUFBMpvN6tSpk/7++2/5+voqMDBQf/zxh0wmk5YtW6b4+Hjt2rVLy5cvd5tI9NChQ/r+++/VsmVLSVKXLl1ks9k0efLkTPex2+2yWq1yOByS0ic6/eqrrzRo0CBXy1QGh8Mhq9WaZc0ZE9n6XOUHaaNHj9aCBQu0bNmyqzoPeY+wBADZSUuTNm9OX67yU0cAQM4kJCSob9++Sk1Nld1u19NPP61Dhw6pYcOG8vLyUpEiRbI8t2/fvnrqqad0xx13SEqfvHTSpEl644039N///tft2Llz5yooKEhBQUEKDg6Wv7+/jh8/rr59+yo4ONhtCQ0NVePGjV3nPv300woPD3ctt99+uySpYcOGbtvbtGlzxfdapUoVPf/885o7d+61frmQR3hmCUDhtXpUzo5LTpVaDk9f/3G45E9XPORv437d7+kSgKtit9slSdHR0YqKilJSUpL27t2rsmXLymazycvLS6tWrdKZM2dcxzds2FAVKlTQ119/rXXr1ikqKsrtmg8//LD69eun5s2ba9GiRWratKmk9O56zz77rCQpNjZWd955p7788kuFh4fr8ccf165du7Ks88KFC+rTp4/69OnjqsNisWjdunUKDw+XJM2cOVNTp07N8hoTJkxQmzZtNHbsWPn7+7u2p6SkyM/P7+q+cLjhaFkCAAAo6BITs15SUnJ+bHJyzo69SitWrJC/v79mzZqle+65R3Xr1tWmTZvk5+en0aNHy+l06u+//9bGjRvVuXNnbd68WbGxsdq4caNefvllTZgwQcWLF5fdbndbhg4dqtdee03NmjVT9+7dlZCQ4Lqn0+lUjx499Nxzz6lZs2YymUyKiYm5Yp1eXjn70/nfx7Vp00ZffPGFJGnQoEE6ePCgW1D67bffVLNmTSVew9cONxZhCQAAoKArUiTrpX1792NLlsz62BYt3I8NDzc+7io9+uijcjgcSktL0/z5812vHQ6HhgwZIpvNpn79+mnUqPQeARMmTNAtt9yiNm3aaNCgQXr77bfl6+sri8WSadm+fbu+++47RUdHuwKK0+nU66+/rgULFmjSpEkKDg7Wfffdp9OnT7t1w3vuuefc6jSZTFf93pxOp1atWqXixYtLkvz8/GQ2u3fuatiwoQIDAzVgwICrvj5uLMISAAAAPMrLy0sXL15UXFycUlJSlJaWpvj4eMXExMhmsykxMVGBgYFu5xQrVkwbNmzQ0KFDtXv3blmtVoWEhGjz5s2y2Wyy2WwaPHiwypcvr/bt22vhwoXy9vZWfHy8OnfurD///FMPPPCAZs2apZiYGP3vf/9T2bJlFRMTo5iYGH344YeZRsfLGBQiO5cfd/DgQSUmJqp27dqSjAOXxWLRtGnTNHXqVP38889X++XDDcQzSwAAAAXdZd3PMvnXCHA6ezbrY//dDe3IkWsu6XJ2u12lS5eWn5+fHA6HUlNTVa5cOdlsNn322Wc6deqUypQpk+m8jHmUAgICdOzYMSUkJOiOO+5wtdycPn1at956q9s5n3/+uY4dO6Zff/1VnTt3vmJd/24B8vf318cff6zx48e7ba9Xr57rWLvd7hr4QZJWr16tUqVKqWLFile8V61atfTss89q69atatas2RWPRd4hLAEAABR0/2qV8cixV2A2mxUdHa2hQ4fqjjvu0A8//KDOnTurSZMmiomJUWhoqEJCQpTy7+erLjNnzhw1aNDA7VmgU6dOuY1mJ0kDBw5U3759MwWhnFi4cKHba6MBHv5t+fLlqlevXo6uP3369Bw/F4W8QVgCAACARzmdTvXs2VNOp1ORkZGS0keee+KJJ/TYY4+pVq1aVzz/r7/+0siRI7Vo0SK37SdOnFD58uUzHZ8RlGw2m2Ety5cv12+//WbYmnW1Ro0apdTU1CseM3LkSAUHB6tXr17XfT/kLsISAGTH7CU9+9CldQBArlq/fr2Sk5P1+eef69tvv5WXl5d69+6tGjVq6JVXXtHbb78tSW4TyXp5ecnpdOr7779X9+7dNWLECNfw4FFRUdq/f7/279/v1iXu3wIDA+Xr6yspPTjZ7XaZTCZNnz5dFy5c0LBhw65Yd8YzTVd6lum2225ze+3l5aVt27apSpUqrmssWbJE9evXv+K94BmEJQDIjsUsdW3i6SoAoMCqW7eu6tatq/nz52vatGkaOnSoTCaTAgIC5OXlpQ4dOkiSrFarJCk1NVV+fn56//33NWnSJH3xxRd68sknXdebPXu2Fi9erLFjx6pcuXJZ3nfp0qWu9YxBIaTM3e2yEh8f76onpx555BH17dtXffv2dW0LCwvTzJkzc3wN5B2T0+l0erqIvBAXF6egoCDFxsaqWLFini4HKLxyOhHslTQecv3XkHKnltyQW+8HHpcbk8H2bVo1X9SRW3Lj/SDnUlJSdPjwYUVERBSKCU7tdrvi4+MVEhLi6VKQD13p/0NOswEtSwCQHYdDOnoufb1iicyjQQEAPMJsNhOUcEMRlgAgO1a79MKE9PUfh0v+Ph4tBwAA5A0+HgUAAAAAA4QlAACAAqaQPJIOXFFu/D8gLAEAABQQFotFkpSUlOThSgDPy/h/kPH/4lrwzBIAAEAB4e3treDgYJ09e1aSFBAQIJPJ5OGqgLzldDqVlJSks2fPKjg4WN7e3td8LcISAABAAVK6dGlJcgUmoLAKDg52/X+4VoQlAACAAsRkMqlMmTIqWbKka5JVoLCxWCzX1aKUgbAEANkxe0kd619aB4CbgLe3d678sQgUZoQlAMiOxSz1bOHpKgAAQB7jI1IAAAAAMEDLEgBkx+GQzsamr5cMkrz4nAkAgMKA3/gAkB2rXerycfpitXu6GgAAkEcISwAAAABggLAEAAAAAAYISwAAAABggLAEAAAAAAYISwAAAABggLAEAAAAAAaYZwkAsuPtJT1W59I6AAAoFAhLAJAdH7P0+mOergIAAOQxPiIFAAAAAAO0LAFAdpxOKTYxfT0oUDKZPFsPAADIE7QsAUB2UmzS4yPTlxSbp6sBAAB5hJYlAPC01aNy5zqNh+TOdYBcNO7X/dd9jb5Nq+ZCJQBw9WhZAgAAAAADhCUAAAAAMEBYAgAAAAADhCUAAAAAMEBYAgAAAAADjIYHANnx9pKa3XtpHQAAFAqEJQDIjo9ZeqODp6sAAAB5jI9IAQAAAMAALUsAkB2nU0qxpa/7WSSTybP1ZCU3JrdlYlvkQ7kxsa3E5LYArh4tSwCQnRSb1HJ4+pIRmgAAQIFHWAIAAAAAA4QlAAAAADBAWAIAAAAAA4QlAAAAADBAWAIAAAAAA4QlAAAAADDAPEsAkB1vk9TgzkvrAACgUCAsAUB2fCzS8C6ergIAAOQxuuEBAAAAgAHCEgAAAAAYICwBQHaSU6WH3kxfklM9XQ0AAMgj+S4sffnll6pQoYICAgLUqFEjHTp0SJIUFRWl2rVrKyQkRAMHDpTT6fRwpQAAAAAKsnwVlg4ePKj33ntPS5Ys0d69e1W5cmV17dpVVqtVrVu3Vq1atbRlyxbt3r1bM2fO9HS5AAAAAAqwfBWW/vrrL0VGRuree+/VLbfcoueff14HDhzQ8uXLFRsbq7Fjx6py5coaOXKkpk+f7ulyAQAAABRg+Wro8OrVq2vVqlXatm2bIiIiNGXKFDVt2lTbt29XZGSkAgICJEk1atTQ7t27r3gtq9Uqq9Xqeh0XF3dDawcAAABQsOSrlqXq1aurQ4cOuueeexQcHKz169frk08+UVxcnCIiIlzHmUwmeXt7Kzo6OstrjRo1SkFBQa6lQoUKefEWAAAAABQQ+Sosbdq0ScuWLdOGDRsUExOjzp0769FHH5XZbJavr6/bsX5+fkpKSsryWkOGDFFsbKxrOX78+I0uHwAAAEABkq/C0rfffqsnn3xSderUUVBQkN5//30dPHhQoaGhOnfunNux8fHx8vHxyfJavr6+KlasmNsCANfE2yTVuS198TZ5uhoAAJBH8tUzSw6HQ+fPn3e9jo+PV1JSksxms9avX+/afvjwYVmtVoWGhnqiTACFjY9FGvWcp6sAAAB5LF+1LNWvX1+LFi3SuHHjNHfuXLVt21alS5fWa6+9pri4OM2YMUOSNHLkSDVp0kTe3t4erhgAAABAQZWvWpbat2+vPXv2aPz48Tp9+rTuvPNO/fDDD7JYLPryyy/VuXNnDRw4UF5eXlqzZo2nywUAAABQgOWrsGQymfTOO+/onXfeybSvTZs2OnjwoLZu3arIyEgVL17cAxUCKJSSU6X2H6SvL3xL8s/6eUkAAFBw5KuwlJ3SpUurZcuWni4DQGGUYvN0BQAAII/lq2eWAAAAACC/ICwBAAAAgAHCEgAAAAAYICwBAAAAgAHCEgAAAAAYuKlGwwMAj/AySTUjLq0DAIBCgbAEANnxtUjjXvR0FQAAII/RDQ8AAAAADBCWAAAAAMAA3fAA3HxWj8rb+yWnSl1Gp6/PHST5++Tt/VGojPt1v6dLAAD8P8ISAOREbJKnKwAAAHmMbngAAAAAYICwBAAAAAAG6IYHIOfy+lkhII/wnBAAwAgtSwAAAABggLAEAAAAAAbohgcA2fEySbeVu7QOAAAKBcISAGTH1yJ99oqnqwAAAHmMbngAAAAAYICwBAAAAAAGCEsAkJ2UVKnz6PQlJdXT1QAAgDzCM0sAkB2npH9iLq0DAIBCgZYlAAAAADBAWAIAAAAAA4QlAAAAADBAWAIAAAAAA4QlAAAAADDAaHgAkB2TpIolL60DAIBCgbAEANnx85Fm9PF0FQAAII/RDQ8AAAAADBCWAAAAAMAAYQkAspOSKnUbn76kpHq6GgAAkEd4ZgkAsuOUdPTspXUAAFAo0LIEAAAAAAYISwAAAABggLAEAAAAAAYISwAAAABggLAEAAAAAAYYDQ8AsmOSVCr40joAACgUCEsAkB0/H+nbQZ6uAgAA5DG64QEAAACAAcISAAAAABggLAFAdqw26eXJ6YvV5ulqAABAHuGZJQDIjsMp7Tt5aR0AABQKtCwBAAAAgAHCEgAAAAAYICwBAAAAgAHCEgAAAAAYICwBAAAAgAFGwwOAnAgK8HQFAAAgjxGWACA7/j7SD297ugoAAJDH6IYHAAAAAAYISwAAAABggLAEANmx2qS+09IXq83T1QAAgDzCM0sAkB2HU9p++NI6AAAoFGhZAgAAAAADhCUAAAAAMEBYAgAAAAADhCUAAAAAMEBYAgAAAAADjIYHADnhZ/F0BQAAII8RlgAgO/4+0k/veroKAACQx+iGBwAAAAAGCEsAAAAAYICwBADZSbVJQ2alL6k2T1cDAADyCM8sAUB20pzSxn2X1gEAQKFAyxIAAAAAGCAsAQAAAIABwhIAAAAAGCAsAQAAAIABwhIAAAAAGCAsAQAAAIABhg4HgOz4+0irRnq6CgAAkMdoWQIAAAAAA/k6LL3xxhtq3bq163VUVJRq166tkJAQDRw4UE4nk0MCAAAAuDHybVjasWOHpkyZogkTJkiSrFarWrdurVq1amnLli3avXu3Zs6c6dkiARQOqTZp+Nz0JdXm6WoAAEAeyZdhyeFwqEePHurbt68qVaokSVq+fLliY2M1duxYVa5cWSNHjtT06dM9XCmAQiHNKf0elb6k0aINAEBhkS/D0ueff66dO3cqPDxcS5cuVWpqqrZv367IyEgFBARIkmrUqKHdu3dneQ2r1aq4uDi3BQAAAAByKt+FpYSEBA0bNkyVKlXS0aNHNW7cONWrV09xcXGKiIhwHWcymeTt7a3o6GjD64waNUpBQUGupUKFCnn1FgAAAAAUAPkuLC1atEiJiYlavXq13n33Xf3666+Kj4/XV199JV9fX7dj/fz8lJSUZHidIUOGKDY21rUcP348L8oHAAAAUEDku3mWTpw4ocjISIWFhUmSzGazatSoob179+rcuXNux8bHx8vHx8fwOr6+vpnCFQAAAADkVL5rWSpfvrySk5Pdth09elTjx4/X+vXrXdsOHz4sq9Wq0NDQvC4RAAAAQCGQ78JSy5YttXv3bn3++ec6ceKEJk6cqO3bt+vxxx9XXFycZsyYIUkaOXKkmjRpIm9vbw9XDAAAAKAgynfd8IoXL66ffvpJAwYMUL9+/VSmTBktWLBAFSpU0JdffqnOnTtr4MCB8vLy0po1azxdLoDCwM8i/Tj80joAACgU8l1YkqQHH3zQrctdhjZt2ujgwYPaunWrIiMjVbx4cQ9UB6DQMZkkf+PnIwEAQMGVL8PSlZQuXVotW7b0dBkAAAAACribLiwBQJ5LtUvjFqev920r+fCjEwCAwiDfDfAAAPlOmkP6+X/pS5rD09UAAIA8QlgCAAAAAAOEJQAAAAAwQFgCAAAAAAOEJQAAAAAwQFgCAAAAAAOEJQAAAAAwwGQhAJAdP4u06M1L6wAAoFC46rCUmpqq1157TZ9//nmWx0yaNEmPPvqoKleufF3FAUC+YDJJwUU8XUXeWD0qd67TeEjuXAfIReN+3X/d1+jbtGouVALgZnHVYclisWjWrFk6deqUypYtq6pVq6pu3bq67777ZDab9eeff2rIkCG6//77CUsAAAAAblpXHZZMJpNCQkLUq1cvnTp1SocOHdLgwYO1f/9+de7cWbNnz9YXX3yhOnXq3Ih6ASDvpdqlz35MX3+5peRDD2YAAAqDHP/GnzFjhipUqKD69evLz89PzZs3d+3btm2b+vfvr88//1y1atVSly5dbkixAOARaQ5pycb09R4tPFsLAADIMzkeDW/Lli3q06ePgoKCdP78eQ0dOlRPPfWUKleurF69eqlTp046f/68KlWqpH79+t3ImgEAAADghstxy9LkyZMlSTt27NDXX3+t9evXa82aNRo8eLBGjBjhOm7KlCmqWbOmOnbsqAceeCD3KwZw9XLroX0gH8qNh/YBADCS47DUv39/xcbG6rbbblN0dLS++eYbvfHGGwoPD1erVq303HPPqXXr1qpfv77eeecdnTx58kbWDQAAAAA3VI674Y0cOVINGjRQQkKCzGaznn76abVq1UovvPCC1q9frzlz5igiIkLVqlXTs88+qw4dOtzIugEAAADghspxy9KTTz4pX19fnT59WqdPn1a1atX0ww8/KDIyUkFBQVq8eLGeeuoprVq1SkePHlXFihVvZN0AAAAAcEPluGXp8ccf12OPPaa6devqwIEDMpvNatu2rerXr6/o6Gj98ccf2rt3rz799FO9/PLLN7JmAAAAALjhchyWHnzwQY0dO1bFihXTY489pmPHjsnPz0+7d++WJL311lsKDQ3V448/ruTkZG3duvWGFQ0AecrXLM0dmL74MscSAACFRY5/669cuVKDBw+W0+nUvn37NGnSJNWvX1+bN2+Wn5+ffv/9d506dUqS9NRTT2ndunWqVavWDSscAPKMl5dUOsTTVQAAgDyW47D04osvSpJSU1PVokULBQYG6j//+Y/CwsK0cOFCSVLZsmUlpbdCVatW7QaUCwAAAAB5I0dhyWq16p577tHu3bvl4+OjUaNGac+ePfLyutSLb/z48erdu7f8/PzUtGlTbdiwQbfffvsNKxwA8ozNLk3/NX39haaSha54AAAUBjn6je/r6yuTyeR6/ddff+mZZ57JdFxoaKgee+wxTZs2jaAEoOCwO6QFf6SvP/ewZPFsOQAAIG/keICHtLQ0JScnS5J8fHzUvn17RUVF6fDhw0pMTFTp0qVVrlw5DRs2TE888cQNKxgAAAAA8kKO+5IcOXJEERERktLDkiSdPn1aNptNO3bs0BdffKFDhw5pwoQJN6ZSAAAAAMhDOQ5LlStX1q5du2S1WtW2bVstWLBADz30kCTJ6XTKZDIpLCxMPXv2lN1uV5cuXW5Y0QAAAABwo+UoLNlsNqWlpUlKf36pTp06Wrx4sby9vWUymeRwOGS1WvXuu+9qyZIlatCggerXr68KFSrc0OIBAAAA4EbJ0TNLZrNZs2fPls1m02effabhw4dLkmbNmqWaNWuqTZs2mj9/vqpXr65q1aqpa9euslh4AhoAAADAzStHYclkMun++++X0+nUpEmTJEnbtm2Tl5eXypcvr88//1z33nuvDh8+LEn6+OOPVbp06RtXNQAAAADcYDl+Zql///7y8fHRhQsX9Oabbyo6OlozZszQ3r17Xd3y7rvvPq1evVo1atS4kTUDQN7yNUvTX7+0DgAACoUc/9YPCQmRr6+vBg0aJEny9vZWsWLFVKpUKXl7e6tnz546ceKE2rVrp61btyo4OPhG1QwAecvLS4oo5ekqAABAHsvxPEuvvvqqYmNjlZCQoISEBKWlpalFixb66aefVKpUKb366qv6+OOPde+992rEiBE3smYAAAAAuOFyHJZMJpMsFossFot8fX1lt9tlsVj04osvatasWerdu7ckafDgwVq4cKGcTucNKxoA8pTNLs38LX2x2T1dDQAAyCM57oYXFBSkYcOGuV7XrVtXFotFnTp1UqdOnWS1WiVJtWrV0rJly2QymXK/WgDwBLtDmr0qfb1TA4nBPgEAKBRy3LL0bw0aNHB77evr61q/6667rr0iAAAAAMgHrjksAQAAAEBBRlgCAAAAAAOEJQAAAAAwQFgCAAAAAAOEJQAAAAAwkOOhwwGg0PIxS1N6XVoHAACFAr/1ASA73l7S7eU9XQUAAMhjdMMDAAAAAAO0LAFAdmx2aeGf6evt60oWfnQCAFAY8BsfALJjd0hTV6SvPxYpWTxbDgAAyBt0wwMAAAAAA4QlAAAAADBAWAIAAAAAA4QlAAAAADBAWAIAAAAAA4QlAAAAADDA0OEAkB0fszS2+6V1AABQKPBbHwCy4+0l3V3J01UAAIA8Rjc8AAAAADBAyxIAZMeeJv1nU/p6q/sls7dn6wEAAHmCsAQA2bGlSROXpa83q0VYAgCgkCAsAQBy3+pR13+NxkOu/xpALhv36/7rvkbfplVzoRIAeYFnlgAAAADAAGEJAAAAAAwQlgAAAADAAGEJAAAAAAwQlgAAAADAAKPhAUB2fLylkc9eWgcAAIUCYQkAsuPtLUXe7ukqAABAHqMbHgAAAAAYoGUJALJjT5N+25a+3uRuyUxXPAAACgPCEgBkx5YmjV6Yvt7wLsISAACFBN3wAAAAAMAAYQkAAAAADBCWAAAAAMAAYQkAAAAADBCWAAAAAMAAYQkAAAAADOTrsNS8eXPNnDlTkrR27VpVq1ZNYWFhGjt2rGcLA1C4+HhLQzunLz4MGw4AQGGRb8PSnDlz9PPPP0uSzp07pzZt2qhz585av3695syZo9WrV3u4QgCFhre31Oiu9MWbsAQAQGGRL8PSxYsX1b9/f912222S0oNT2bJl9c477+jWW2/V0KFDNX36dA9XCQAAAKAgM3u6ACP9+/dXu3btlJycLEnavn27GjduLJPJJEm6//77NXjw4Ctew2q1ymq1ul7HxcXduIIBFGxpadIfu9PX61endQkAgEIi34Wl1atXa+XKldq1a5d69+4tKT3oVK9e3XVMsWLFdOrUqSteZ9SoUXr33XdvaK1Anlg9ytMVIDVNeu/b9PUfh0v+hKXcsP7QhSvu32Dfn0eVAABgLF91w0tJSdFLL72kzz77TEWLFnVtN5vN8vX1db328/NTUlLSFa81ZMgQxcbGupbjx4/fsLoBAAAAFDz5qmVpxIgRql27tlq2bOm2PTQ0VOfOnXO9jo+Pl4+PzxWv5evr6xawAAAAAOBq5KuwNHfuXJ07d07BwcGSpKSkJC1YsECSVLduXddxf/31l8qVK+eJEgEAAAAUEvkqLP3xxx+y2+2u1wMGDFBkZKS6du2qChUq6LffflPDhg01evRoNWvWzIOVAgAAACjo8lVYKl++vNvrIkWKKCwsTGFhYRo3bpweffRRFSlSRMHBwa7JagEAAADgRshXYenfLg9EPXv2VLNmzbR3717Vr19fRYoU8VxhAAAAAAq8fB2W/i0iIkIRERGeLgNAYWPxlga1v7QOAAAKhZsqLAGAR5i9pea1PF0FAADIY/lqniUAAAAAyC9oWQKA7KSlSZv/Tl+vfavkTVc8AAAKA8ISAGQnNU16c3b6+o/DJX/CEgAAhQHd8AAAAADAAC1LwI2yepSnKwBumPWHLni6BAAAbjhalgAAAADAAGEJAAAAAAwQlgAAAADAAGEJAAAAAAwwwAMAZMfiLb3W+tI6AAAoFAhLAJAds7fU9gFPVwEAAPIY3fAAAAAAwAAtSwCQnTSHtPNI+vpd4ZI3nzMBAFAYEJYAIDupdqnfl+nrPw6X/H08Wg4AAMgbfDwKAAAAAAYISwAAAABggLAEAAAAAAYISwAAAABggLAEAAAAAAYISwAAAABggKHDASA7Zi+pR/NL6wAAoFAgLAFAdixm6ckGnq4CAADkMT4iBQAAAAADtCwBQHbSHNLfp9LXby0refM5EwAAhQFhCQCyk2qXek1JX/9xuOTv49FyAABA3uDjUQAAAAAwQFgCAAAAAAOEJQAAAAAwQFgCAAAAAAOEJQAAAAAwwGh4AIB8KfLY1Ou+xoZbeuRCJUDuGvfr/ly5Tt+mVXPlOgCyRlgCgOyYvaRnH7q0DgAACgXCEgBkx2KWujbxdBUAACCP8REpAAAAABigZQkAsuNwSEfPpa9XLCF58TkTAACFAWEJALJjtUsvTEhf/3G45O/j0XIAAEDe4ONRAAAAADBAWAIAAAAAA4QlAAAAADBAWAIAAAAAA4QlAAAAADBAWAIAAAAAAwwdDgDZMXtJHetfWgcAAIUCYQkAsmMxSz1beLoKXIPIY1Nz5TobbumRK9cBctO4X/df9zX6Nq2aC5UABRcfkQIAAACAAVqWACA7Dod0NjZ9vWSQ5MXnTAAAFAb8xgeA7FjtUpeP0xer3dPVAACAPEJYAgAAAAADhCUAAAAAMEBYAgAAAAADhCUAAAAAMEBYAgAAAAADhCUAAAAAMMA8SwCQHW8v6bE6l9YBAEChQFgCgOz4mKXXH/N0FQAAII/xESkAAAAAGKBlCQCy43RKsYnp60GBksnk2XoAAECeoGUJALKTYpMeH5m+pNg8XQ0AAMgjhCUAAAAAMEBYAgAAAAADhCUAAAAAMEBYAgAAAAADhCUAAAAAMEBYAgAAAAADzLMEANnx9pKa3XtpHQAAFAqEJQDIjo9ZeqODp6uAB0Uem3rd19hwS49cqATIXeN+3Z8r1+nbtGquXAfIb/iIFAAAAAAM0LIEANlxOqUUW/q6n0UymTxbDwAAyBO0LAFAdlJsUsvh6UtGaAIAAAUeYQkAAAAADBCWAAAAAMAAYQkAAAAADBCWAAAAAMAAYQkAAAAADOTLsLRkyRJVqlRJZrNZd999t/bs2SNJioqKUu3atRUSEqKBAwfK6XR6uFIAAAAABVW+C0sHDx5Ut27d9OGHH+rkyZOqWrWqunfvLqvVqtatW6tWrVrasmWLdu/erZkzZ3q6XACFgbdJanBn+uLNHEsAABQW+S4s7dmzRx9++KE6duyoUqVK6eWXX9Zff/2l5cuXKzY2VmPHjlXlypU1cuRITZ8+3dPlAigMfCzS8C7pi4/F09UAAIA8YvZ0Af/WqlUrt9f79u3Trbfequ3btysyMlIBAQGSpBo1amj37t1ZXsdqtcpqtbpex8XF3ZiCAQAAABRI+a5l6XKpqakaM2aMevbsqbi4OEVERLj2mUwmeXt7Kzo62vDcUaNGKSgoyLVUqFAhr8oGAAAAUADk67A0bNgwBQYGqnv37jKbzfL19XXb7+fnp6SkJMNzhwwZotjYWNdy/PjxvCgZQEGUnCo99Gb6kpzq6WoAAEAeyXfd8DKsWrVKkydP1oYNG2SxWBQaGqqoqCi3Y+Lj4+Xj42N4vq+vb6ZwBQAAAAA5lS9blg4fPqzOnTtr8uTJql69uiSpdu3aWr9+vdsxVqtVoaGhnioTAAAAQAGW71qWkpOT1apVKz322GNq166dEhISJEn169dXXFycZsyYoW7dumnkyJFq0qSJvL29PVwxCqTVozxdAXDDrD90wdMlAABwU8h3YemXX37R7t27tXv3bk2bNs21/fDhw/ryyy/VuXNnDRw4UF5eXlqzZo3nCgUAAABQoOW7sPTYY4/J6XQa7gsPD9fBgwe1detWRUZGqnjx4nlcHQAAAIDCIt+FpeyULl1aLVu29HQZAAAAAAq4my4sAUCe8zZJdW67tA4AAAoFwhIAZMfHIo16ztNVAACAPJYvhw4HAAAAAE8jLAEAAACAAcISAGQnOVV6dFj6kpzq6WoAAEAe4ZklAMiJFJunKwAAAHmMliUAAAAAMEBYAgAAAAADhCUAAAAAMEBYAgAAAAADhCUAAAAAMMBoeACQHS+TVDPi0joAACgUCEsAkB1fizTuRU9XAQAA8hjd8AAAAADAAGEJAAAAAAwQlgAgO8mpUrv305fkVE9XAwAA8gjPLAFATsQmeboCAACQx2hZAgAAAAADhCUAAAAAMEBYAgAAAAADhCUAAAAAMEBYAgAAAAADjIaHgmf1KE9XgILGyyTdVu7SuoesP3TBY/cGAKAwIiwBQHZ8LdJnr3i6CgAAkMfohgcAAAAABghLAAAAAGCAbngAkJ2UVKnb+PT1GX0kPx9PVoObVOSxqdd9jQ239MiFSoDcN+7X/dd9jb5Nq+ZCJUDuIiwBQHackv6JubQOAAAKBbrhAQAAAIABwhIAAAAAGCAsAQAAAIABwhIAAAAAGCAsAQAAAIABRsMDgOyYJFUseWkdAAAUCoQlAMiOn0/6/EoAAKBQoRseAAAAABggLAEAAACAAcISAGQnJVXqNj59SUn1dDUAACCP8MwSAGTHKeno2UvrAACgUKBlCQAAAAAMEJYAAAAAwABhCQAAAAAMEJYAAAAAwABhCQAAAAAMMBoeAGTHJKlU8KV1AABQKBCWACA7fj7St4M8XQUAAMhjdMMDAAAAAAOEJQAAAAAwQDc8AMiO1Sb1mZq+Pr6H5GvxbD3AdYo8NvW6r7Hhlh65UAmQu8b9uj9XrtO3adVcuQ5ufoQlAMiOwyntO3lpHQAAFAp0wwMAAAAAA4QlAAAAADBANzzkH6tHeboC4IZZf+iCp0sAAABXiZYlAAAAADBAWAIAAAAAA3TDA4CcCArwdAUAACCPEZYAIDv+PtIPb3u6CgAAkMfohgcAAAAABghLAAAAAGCAsAQA2bHapL7T0herzdPVAACAPMIzSwCQHYdT2n740joAACgUaFkCAAAAAAOEJQAAAAAwQFgCAAAAAAOEJQAAAAAwwAAPkFaP8nQFwA2x/tCFXLmOl9WmOv+/vvHIRTl8LblyXeBqRR6b6ukSgBtm3K/7PV0CkAlhCQByIM2HH5cAABQ2/PYHgGw4fC3aNOV1T5cBAADyGM8sAQAAAIABwhIAAAAAGKAbHgBkw2Sz67YpSyVJ+3q1kdPCj04AAAoDfuMDQDZMDqdCdh52rTs9XA8AAMgbdMMDAAAAAAOEJQAAAAAwcNN1w4uKilK3bt104MABde/eXaNHj5bJZPJ0WVcvNyaCbTzk+q8B3AC5MRnsA5WK50IlAG6U/DRB7oZbeni6BJfc+Lrkp/dTWOWXCXL7Nq3q6RJccuNrkp/eT07dVC1LVqtVrVu3Vq1atbRlyxbt3r1bM2fO9HRZAAAAAAqgmyosLV++XLGxsRo7dqwqV66skSNHavr06Z4uCwAAAEABdFN1w9u+fbsiIyMVEBAgSapRo4Z2795teKzVapXVanW9jo2NlSTFxcXd+EJzIjHl+q+RW+8lN2oBLpOYbM3+oGzE5cL3ZW7UIUleVpsy/rclJlvlcDhy5boAckdKYoKnS3DJjZ87+en9wLPyzd+typ3vy/z0fjJqcTqvPMatyZndEflI//79lZKSosmTJ7u2lShRQvv371dISIjbscOHD9e7776b1yUCAAAAuEkcP35c5cuXz3L/TdWyZDab5evr67bNz89PSUlJmcLSkCFD1K9fP9drh8Ohixcvqnjx4jfngBC4JnFxcapQoYKOHz+uYsWKeboc3MT4XkJu4XsJuYXvJeSWwvi95HQ6FR8fr7Jly17xuJsqLIWGhioqKsptW3x8vHx8fDId6+vrmylYBQcH38jykI8VK1as0Pznx43F9xJyC99LyC18LyG3FLbvpaCgoGyPuakGeKhdu7bWr1/ven348GFZrVaFhoZ6sCoAAAAABdFNFZYaNGiguLg4zZgxQ5I0cuRINWnSRN7e3h6uDAAAAEBBc1N1wzObzfryyy/VuXNnDRw4UF5eXlqzZo2ny0I+5uvrq2HDhmXqkglcLb6XkFv4XkJu4XsJuYXvpazdVKPhZThz5oy2bt2qyMhIFS9e3NPlAAAAACiAbsqwBAAAAAA32k31zBIAAAAA5BXCEgAAAAAYICyhwFuyZIkqVaoks9msu+++W3v27PF0SQAKKX4eIbc1b95cM2fO9HQZKADeeOMNtW7d2tNl5DuEJRRoBw8eVLdu3fThhx/q5MmTqlq1qrp37+7psnCTiYqKUu3atRUSEqKBAweKRz1xLfh5hNw2Z84c/fzzz54uAwXAjh07NGXKFE2YMMHTpeQ7hCUUaHv27NGHH36ojh07qlSpUnr55Zf1119/ebos3ESsVqtat26tWrVqacuWLdq9ezef4uKa8PMIuenixYvq37+/brvtNk+Xgpucw+FQjx491LdvX1WqVMnT5eQ7N9U8S8DVatWqldvrffv26dZbb/VQNbgZLV++XLGxsRo7dqwCAgI0cuRIvfLKK+rWrZunS8NNhp9HyE39+/dXu3btlJyc7OlScJP7/PPPtXPnTvXo0UNLly5V8+bN5ePj4+my8g1allAgtG3bVsHBwZmWTz/91HVMamqqxowZo549e3qwUtxstm/frsjISAUEBEiSatSood27d3u4Ktzs+HmE67F69WqtXLlSo0eP9nQpuMklJCRo2LBhqlSpko4ePapx48apXr16hPDL0LKEAuGLL74w/I8dGhrqWh82bJgCAwN5RgBXJS4uThEREa7XJpNJ3t7eio6OVkhIiAcrw82Mn0e4VikpKXrppZf02WefqWjRop4uBze5RYsWKTExUatXr1ZYWJjsdrvuuusuff311+rRo4eny8sXCEsoEEqVKnXF/atWrdLkyZO1YcMGWSyWPKoKBYHZbJavr6/bNj8/PyUlJRGWcE34eYTrMWLECNWuXVstW7b0dCkoAE6cOKHIyEiFhYVJSv+dV6NGDR04cMDDleUfhCUUeIcPH1bnzp01efJkVa9e3dPl4CYTGhqqqKgot23x8fH058Y14ecRrtfcuXN17tw5BQcHS5KSkpK0YMECbdq0SVOmTPFscbjplC9fPlPPnKNHj6pu3boeqij/MTkZAxcFWHJysu677z49+OCDGjt2rGt7YGCgTCaTByvDzWLVqlXq0aOH61O2w4cPq3r16kpISJC3t7eHq8PNhJ9HyA0nTpyQ3W53vR4wYIAiIyPVtWtXV+sAkFMXLlxQpUqV9NFHH6lVq1ZatGiR3njjDe3fv18VKlTwdHn5AgM8oED75ZdftHv3bk2bNk1FixZ1LUePHvV0abhJNGjQQHFxcZoxY4YkaeTIkWrSpAlBCVeNn0fIDeXLl1d4eLhrKVKkiMLCwghKuCbFixfXTz/9pFmzZqlq1aqaMGGCFixYQFC6DC1LAJCNpUuXqnPnzvL395eXl5fWrFlDFyoAAAoBwhIA5MCZM2e0detWRUZGqnjx4p4uBwAA5AHCEgAAAAAY4JklAAAAADBAWAIAAAAAA4QlAAAAADBAWAIA5Hvnzp3Tpk2brvn8fz+em5aWlmnbv128eNHtdWpqqhISEq65BgDAzYewBADI97Zu3aqmTZvqjz/+kCQ98cQTKlWqlNt8M2XKlFGzZs0ynWu323Xffffpr7/+cm1buHCh6tWrp7S0NMP7paSkqHLlylqyZIlr2++//64SJUpkmu0eAFBwEZYAAPle8+bNNXToUD377LNKS0uTxWLRrFmzdOTIEdfyww8/yM/Pz3VOamqqHA6HzGaznnjiCa1YscK1b8qUKerWrZu8vb2VlpYmu93udr+lS5eqZMmSunDhgipUqKDw8HA9/fTTstlsqlatmsLDw1W+fHlNmTIlz74GAIC8x9DhAICbxpEjRxQeHq6nnnpKzzzzjJo3b+7at2HDBo0aNcrVGtSyZUtt27ZNFotFUnoL06lTp3TLLbe4XdNms2nQoEF6/fXXJaV32atZs6Z69Oihnj17SpLMZrO++eYbffrpp9qwYYPrPJPJJLPZfMPfNwDAM/gJDwDI1y5evKgTJ07Iy8vLFXRKly6tAQMGaMCAAW7HPvjgg671H3/8UVarVb6+vpKkVatWqU+fPtqxY4frGLvdLrvd7tYi9dVXX2nnzp0qXbq0zGaz3nrrLf388886d+6cYmJidN9990mSBg8erA4dOtyw9w0A8DzCEgAgX4uKitL777+vrVu3atasWXr00Uc1YsQIffzxx/Lycu9NbrPZ3AJS+fLlFRAQIJPJpAsXLshisSg8PNx1fFpamipUqKA///xTUnrLVf/+/VWqVCnXMcePH1f37t1drUyS1LNnT8XFxd3Adw0AyA8ISwCAfK1Bgwb65Zdf1KhRI5nNZh04cEBt2rSRj4+P0tLStGfPHtWoUUNOp1N2u12dO3fWkCFD5HQ6de7cOUnpXeuqVq2qadOmqVGjRm7XdzqdSk1NlY+PjxYvXqxWrVopJibGtd/Ly0tDhw7VJ5984tp27tw5RUZG5sXbBwB4EGEJAHBTqVq1qvbu3StJ2rt3ryIjI7Vt2za3Y7799lv1799fFotFJpNJ58+fl5eXl7p27Zrpek6nU6VKldKmTZv0+uuvKykpSZ06dXI75r333svUsgQAKPgISwCAm8pLL72kxYsXy9/fX8nJyYqPj9ctt9wiLy8vWa1WJSQkaO3atTp16pQk6dixY6pbt65++ukn1ahR44rXNplMCgwMzLR9xIgR+vTTT12vT506RcsSABQCDB0OALhp7N27V+3atdM///yjI0eO6M4771R4eLg6duyoI0eO6PTp04qPj9e9994rSTp58qQeeeQRVa1aVQ0bNtQtt9yiEiVKqGzZsgoPD1dYWJhb97qsvPPOO4qKinItHTt2vNFvFQCQDxCWAAA3BZvNpjfeeEMHDx6UJH344Yc6fvy4fv/9d82fP1/z5s1zO37ZsmW677779Morr2jVqlWKjo7WsWPHVKdOHb333ns6cuSIzp8/n2lEPSMjRozQnXfe6VoWLFhwQ94jACB/oRseACDfi4uL0549ezR+/Hg1b95cPXr00NKlS7V27VqVK1dOCxcuVKtWrfSf//xHL730krZv365BgwZp5syZat++fbbXT0tLk7e3t9vr1NRU2Ww2SektS0bPLF0+8h4AoOBhUloAwE3h4MGDCgsL0x133KFGjRppzJgxbkN8nzlzRu+88442btyo9evX68CBAypevLgiIiJcw4dLksPhkMlkcr22Wq165plnNHXqVNe1Hn74YdWrV09ffPGFfH19XcdezuFwyGw269ChQzf4nQMAPIWwBAC4qSQnJ8vf3z/L/U6n0zDcAABwtQhLAAAAAGCAAR4AAAAAwABhCQAAAAAMEJYAAAAAwABhCQAAAAAMEJYAAAAAwABhCQAAAAAMEJYAAAAAwABhCQAAAAAMEJYAAAAAwMD/AXmXtyD+XVp0AAAAAElFTkSuQmCC\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 3
  },
  {
   "metadata": {},
   "cell_type": "code",
   "outputs": [],
   "execution_count": null,
   "source": "",
   "id": "51f6cd036a6e3269"
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
